Gas Path Research Articles

Fractional Cumulative Residual Mean Relative Entropy and Its Application in an Aeroengine Gas Path System

Mean relative entropy has a wide range of applications in measuring information differences. However, relative entropy is difficult to approximate from empirical distribution entropy. Therefore, we replace the probability density function in the mean relative entropy with the residual distribution function and add the form of fractional-order calculation, named fractional-order cumulative residual mean relative entropy. The fractional cumulative residual average relative entropy can be approximated by the empirical entropy of the sample data, and the fractional calculation form is beneficial to revealing the details and information of the underlying system. Some statistical properties of the new entropy are given. Empirical fractional cumulative residual mean relative entropy is shown to converge to the theoretical value. Finally, fractional cumulative residual mean relative entropy is used to analyze aeroengine gas path data.

Noise Reduction of Gas Turbine Unit Gas Paths by Lining Their Turns

Specific features of reducing the noise emitted from gas turbine unit (GTU) gas paths by lining their turns are analyzed. This problem is relevant for high-capacity GTUs when their gas paths cause exceeding of sanitary standards in the surrounding area. Methods for reducing the noise of gas paths by using various types of silencers are considered. One of the methods is to line the GTU exhaust path turns with sound-absorbing material. The noise suppression effect obtained from the lining of gas paths turns is compared with the effects obtained from using the known methods. It is shown that the lining of gas path turns allows the noise level to be additionally reduced while featuring the minimal pressure drop in comparison with that in using other silencers. A technical solution for reducing noise by lining for GTUs is given. The additional noise level reduction obtained in the case of lining the GTU gas path turn with sound-absorbing panels was up to 8 dBA. For the GTU exhaust paths in which the flow velocity in the gas conduits is 30–50 m/s at temperatures of 300–450°C, the efficiency decreases by 12–20%, respectively, for the above-mentioned velocity variation limits. To determine the pressure drop in turns of a complex shape, which are encountered in real GTU paths, mathematical simulation was used. For the problem considered, the simulation was carried out in the Solidworks Flow Simulation software, using which the pressure drop values were determined. Methods for additionally decreasing the pressure drop across the lined turn by fitting it with non-profiled blades were analyzed. It has been found that the installation of non-profiled blades in a direct turn makes it possible to reduce the turn pressure drop coefficient by 1.63–1.7 times in comparison with the original version and by 2.5–2.6 times in comparison with the lining without the use of blades. The effect the number of blades has on the turn pressure drop was studied. It has been shown that with increasing the number of blades from 3 to 4, the local pressure drop coefficient remains almost unchanged.

Экспериментальное исследование накопления углеродных отложений в кислородно-метановом модельном газовом тракте

The paper considers mechanisms of the carbon deposits formation on the metal surface at contact with the gas phase containing products of incomplete combustion of the oxygen-methane generator gas. The first mechanism is the socalled mechanism of metal dust formation, which products remain on the wall surface and form the carbon deposits, the second is the mechanism of carbon deposits formation associated with the carbon particles in the gas flow, which are being deposited on the wall. An experimental system was developed with the working section being a model path of the oxygen-methane generator gas of the reducing composition; and accumulation of the carbon deposits was experimentally studied. When selecting performance characteristics of the experimental system, features of the liquid rocket engine gas path were taken into account; therefor, the experimental system was having characteristics closer to the expected characteristics of the full-scale gas path. Intensities of the deposit formation on samples of metallic material and reference quartz were compared. It was established that the main mechanism for the carbon deposits formation was precipitation of soot contained in the generator gas flow onto the wall of the gas path. The number of deposits was determined by weight. The range of the fuel components ratio was identified, where formation of the deposits was minimal

Design and fabrication of a chalcogenide hollow-core anti-resonant fiber for mid-infrared applications.

Chalcogenide hollow-core anti-resonant fibers (HC-ARFs) are a promising propagation medium for high-power mid-infrared (3-5 µm) laser delivery, while their properties have not been well understood and their fabrications remain challenging. In this paper, we design a seven-hole chalcogenide HC-ARF with touching cladding capillaries, which was then fabricated from purified As40S60 glass by combining the "stack-and-draw" method with a dual gas path pressure control technique. In particular, we predict theoretically and confirm experimentally that such medium exhibits higher-order mode suppression properties and several low-loss transmission bands in the mid-infrared spectrum, with the measured fiber loss being as low as 1.29 dB/m at 4.79 µm. Our results pave the way for the fabrication and implication of various chalcogenide HC-ARFs in mid-infrared laser delivery systems.

Effects of Part-to-Part Flow Variations on Overall Effectiveness and Life of Rotating Turbine Blades

Abstract As firing temperatures in gas turbine engines continue to increase to achieve high efficiencies, components in the main gas path must be protected with cooling flows to ensure lifing targets are met. Manufacturing variations, however, influence the performance and life characteristics of components with the same nominal design. This study presents blade flow and overall cooling effectiveness measurements for nine true-scale, aero engine turbine blades with realistic manufacturing variations. Flow measurements were made through each blade at a fixed pressure ratio to determine flow variability between holes and between blades. Infrared thermography was used to capture spatially-resolved temperature measurements reported as overall effectiveness on the same nine blades under high-speed rotating conditions at the Steady Thermal Aero Research Turbine Laboratory. Thermal performance was correlated with blade flow performance indicating substantial blade-to-blade variations resulting from manufacturing differences. Measurements also indicated wide variations in cooling jet trajectories as well as overall cooling effectiveness. Finally, the observed blade-to-blade variations in effectiveness were scaled to engine conditions with lifing estimates showing some blades would be expected to last only half as long as others due to manufacturing variability.

Convolutional Neural Network Denoising Auto-Encoders for Intelligent Aircraft Engine Gas Path Health Signal Noise Filtering

Abstract Removing noise from health signals is critical in gas path diagnostics of aircraft engines. An efficient noise filtering/denoising method should remove noise without using future data points, preserve important changes, and promote accurate diagnostics without time delay. Machine learning (ML)-based methods are promising for high fidelity, accuracy, and computational efficiency under the motivation of Intelligent Engines. However, previous ML-based denoising methods are rarely applied in actual engineering practice because they cannot accommodate time series and cannot effectively capture important changes or are limited by the time delay problem. This paper proposes a convolutional neural network denoising auto-encoder (CNN-DAE) method to build a denoising auto-encoder structure. In this structure, a convolutional operation is used to accommodate time series, and causal convolution is introduced to solve the problem of using future data points. The proposed denoising method is evaluated against NASA's propulsion diagnostic method evaluation strategy (prodimes) software. It has been proved that the proposed method can accommodate time series, remove noise for improved denoising accuracy, and preserve the important changes for enhanced diagnostic information. NASA's blind test case results show that kappa coefficient of a common diagnostic method using the processed data is 0.731 and is at least 0.046 higher than the other diagnostic methods in the open literature. Processing health signals using the proposed method would significantly promote accurate diagnostics without time delay. The proposed method could support intelligent condition monitoring systems by exploiting historical information for improved denoising and diagnostic performance.

Three Shaft Industrial Gas Turbine Transient Performance Analysis.

The power demand from gas turbines in electrical grids is becoming more dynamic due to the rising demand for power generation from renewable energy sources. Therefore, including the transient data in the fault diagnostic process is important when the steady-state data are limited and if some component faults are more observable in the transient condition than in the steady-state condition. This study analyses the transient behaviour of a three-shaft industrial gas turbine engine in clean and degraded conditions with consideration of the secondary air system and variable inlet guide vane effects. Different gas path faults are simulated to demonstrate how magnified the transient measurement deviations are compared with the steady-state measurement deviations. The results show that some of the key measurement deviations are considerably higher in the transient mode than in the steady state. This confirms the importance of considering transient measurements for early fault detection and more accurate diagnostic solutions.

Prediction of the breakdown voltage and breakdown area of gas switches based on ionization integral

Gas spark switches have a simple structure and high current capacity and are widely used in the field of pulsed power. The breakdown path of gas switches affects their jitter and lifetime. Particle simulations are used to analyze the breakdown path, which requires a large amount of computation resources. In this paper, in order to calculate the ionization integral value of electrode gaps, a simulation-based method using a simplified model is studied. The integration of the ionization coefficient along the E-field curves is calculated for the electrode gap and is used to determine if breakdown occurs for a given curve. The breakdown region of two-electrode self-breakdown switches is estimated using the distribution of breakdown curves, and the trigger voltage of a three-electrode gas-trigger switch is estimated by analyzing the curves. By applying the ionization integral value to different paths to reach the streamer formation condition as the breakdown criterion, the operating voltage and erosion region of the electrodes are estimated. The numerical results for an environmental pressure of 0.2 MPa are in good agreement with the experimental results from a triggering experiment that uses a three-electrode gas-triggered switch. This ionization integral model can be used to predict the breakdown voltage and breakdown region of gas switches, which is conducive to improving the performance of gas switches.

Saving of Coke Oven Gas by Reduction of Smoke Pushing of Recovery Type Coke Plant

For stable oven operation and prolongation of the coke oven life, it is important to remove excess carbon formation on the coke oven wall. It is considered that the carbon formation rate is influenced by the gas components generated during carbonation, the gas velocity and oven wall temperature are not uniformly maintained, as a result of smoke pushing. The smoke pushing is not favourable for the good health of the coke oven battery. In this paper, the smoke pushing can be rectified by proper maintenance of the gas path. Energy consumption and economic growth are interwoven, and rising energy levels always represent rising energy consumption. Coke is a reducing agent and a load-handling tool in blast furnaces. By this rectification, the coke oven gas flow was reduced from 17600Nm3/hrs to 17300Nm3/hrs without any extra manpower cost. The experimental set-up implementation of this modern proposal in a coke plant will make coke more extra energy efficient with no other extra costs.

Experimental investigation of wall-to-bed heat transfer of carbon nanotubes in a fluidized bed

Wall-to-bed heat transfer characteristics of multi-walled carbon nanotubes (MWCNTs) were determined in a fluidized bed (0.15 m i.d. by 2.0 m height). Two types of CNTs with different nanotube shapes were used: entangled CNTs (ENCNTs) and vertically aligned CNTs (VACNTs). The flow regimes of MWCNTs were identified as fixed bed, partial fluidization, and complete fluidization from the pressure drop across the bed (ΔP) with gas velocity. In the partial fluidization regime, different gas channeling phenomena occurred depending on the nanotubes shape on the CNT particles, affecting the bed hydrodynamics. The instantaneous surface temperature (Tsi) of the heat transfer probe decreased and its fluctuation increased with the gas velocity proportional to the bed particle movement near the wall. Fluctuations in ΔP and Tsi at the wall had a strong correlation for all MWCNTs, and the wall-to-bed heat transfer was greatly influenced by the movement of particles induced by a preferential flow path of gas in the bed such as gas channeling and bubbles. Fluctuations in ΔP and Tsi of VACNTs were considerably lower than those of ENCNTs because of the formation of a chain-like network structure of the bed. The wall-to-bed heat transfer coefficient (hw) in the CNT fixed bed was considerably higher than that of comparable particles owing to their high conductivity. The average hw of the CNTs increased with gas velocity, and the rate of increase depended on the shape of the nanotubes. The hw of the VACNTs which form easily tangled agglomerates by many long nanotubes, was lower than that of the ENCNTs. Correlations for hw prediction were firstly developed for the partial and complete fluidization regimes. The predicted values well accorded with the experimental results, and the hw changes of the MWCNTs with gas velocity could be predicted well based on the proposed correlation and two-phase model of the bubbling fluidized bed.

Diagnostics using a physics-based engine model in aero gas turbine engine verification tests

In the present study, the application of a diagnostic method using a physics-based model is proposed during engine verification testing. A physics-based engine model is constructed, based on a 0-dimensional system analysis method, and then revised through performance adaptation with a basic engine model. Adaptation factors are used for the compressor, secondary air system, nozzle, exhaust gas temperature, and engine thrust. Gas path analysis is conducted using the physics-based engine model and the performance test data in real time. A health parameter that can quantitatively evaluate the performance difference of components was defined. Health parameters for the compressor capacity and efficiency, secondary air system, and nozzle are calculated from the gas path analysis. The multi-variable Newton–Raphson method is employed for the performance adaptation and gas path analysis in real time. A single-shaft gas turbine engine, which is constructed based on the core part of a turbofan engine currently under development, is utilized to test and evaluate the effectiveness of the proposed method. Three tests are performed for engine verification. The proposed diagnostic method is applied to the aero gas turbine engine verification test. In 33 test cases, the fault detection rates for the compressor's variable guide vane, secondary air system, and variable area nozzle are 100%, 91%, and 79%, respectively. As a result, it is confirmed that the proposed method can simultaneously detect abnormalities in the compressor's variable guide vane, secondary air system, and variable area nozzle. In addition, this study indicates that applying the physics-based engine model to the diagnostics logic can effectively detect failures with a small amount of data.

Toward a Stackable CO2-to-CO Electrolyzer Cell Design─Impact of Media Flow Optimization

Aqueous CO2-to-CO electrolysis is a promising technology for closing the carbon cycle and defossilizing industrial processes. Considering the technological readiness, consensus has been achieved about using silver as a stable and selective electrocatalyst for the CO2-to-CO reduction reaction in aqueous electrolyte. On the other hand, challenges such as media flow management, component stability, and force distribution are still associated with improving the process performance and developing a stackable cell concept to meet industrially relevant levels. We therefore report on a promising stack concept with continuous flowcells operated with gas diffusion electrodes (GDEs). To enhance the CO2-to-CO conversion efficiency, dedicated media flow chambers were developed on two levels. In the gas chamber, which touches the GDE from the far side of the anode, the feed gas flow and distribution over the GDE were controlled by introducing various gas path architectures in a modular flowcell. In addition, an ionically conductive spacer was implemented in the catholyte chamber, which is adjacent to the opposite side of the GDE. The effect of these modifications on the cell voltage, selectivity, and overall conversion was investigated at 100 mA/cm2 with varying CO2 feed gas flow and concentration. Noteworthy, an optimized feed gas distribution generated an increase of the Faraday efficiency for CO under reduced CO2 supply. Furthermore, the implementation of the spacer enhanced the process stability by suppressing gas-bubble-induced noise in the cell voltage measurements. By functioning as support structures to the GDE, the combined modifications provided the cell with mechanical integrity and allowed an ionic and electric contact over the full active cell area, which is required for both stacking and upscaling of the cell. The corresponding performance was demonstrated by a two-cell short-stack.

Gas path diagnosis method for gas turbine fusing performance analysis models and extreme learning machine

The gas path analysis, which can quantify the performance degradation of gas turbine components, has been extensively applied to the gas path diagnosis. However, the precondition of this method is that the number of measurable parameters for the gas turbine to be diagnosed should not be less than the number of its health factors. In the existing research, this precondition can be guaranteed through common approaches such as screening the degraded components by a model-based prediagnosis process or recognizing the degraded components by using tools such as an ANN or a support vector machine. However, the diagnosis speed, recognition accuracy, and robustness of these approaches need to be improved. Therefore, a diagnosis method fusing the gas path performance analysis model and the extreme learning machine was proposed in this paper and applied to a GE LM2500+SAC gas turbine. The working mechanism of similarity ranking-gas path diagnosis-rationality check was introduced in the fusion method, endowing it with a higher recognition accuracy rate, stronger robustness, and higher diagnostic accuracy.

A film-linked electrostatic self-assembly microfluidic chip.

This article proposes a film-linked electrostatic self-assembly microfluidic chip for the first time, designed to be ready-to-use. Barrier films are used to isolate the gas/liquid path microchannels and the pre-stored reagents of the chip before use. Through the linkage design between the film materials, the motion of barrier films is linked to the structural changes inside the chip. Under the combined action of the rebound force of the elastic substrate, the electrostatic adsorption force between the substrates, and the reaction force of the elastic film, the elastic substrate and the liquid storage substrate are instantly bonded, and the self-assembly of the chip is completed within 1 s. By using six independently output programmable sequences to perform the sequential quantitative pumping of pre-stored reagents, the transfer and mixing of samples and pre-stored reagents are automatically driven in a confined space, which greatly reduces the contamination risk and loss rate of samples/reagents, and improves the accuracy and reproducibility of test results. In addition, the microfluidic multi-step reaction driven in parallel can avoid liquid reflux, accurately control the amount of reactant transfer, and realize the quantitative detection of samples. Multiple reactions can be performed synchronously without interference, saving the test time. Since each gas path is independently controllable, the chip can be extended to a variety of biochemical reactions and has the potential to detect a variety of substances.

Distribution of PCDD/F and PCB at Different Positions of Circulating Fluidized Bed Municipal Solid Waste Incinerators

Because of a high moisture content and a low heating value of Chinese municipal solid waste (MSW), circulating fluidized bed (CFB) incinerators have been widely adopted in China for incinerating MSW since 1998. In this study, two typical CFB incineration plants (A and B) were investigated for contents and fingerprints of PCDD/F and PCB at different positions downstream their post-combustion zone, aiming to draw a full picture of formation and distribution of these organochlorinated pollutants. Both flue gas and ashes were sampled at five different positions of Plant A, from high-temperature superheater to outlet of baghouse filter, representing a huge range of flue gas temperatures; for Plant B, five ash samples were collected at different positions of the waste heat boiler (from high-temperature superheater to lower economizer). A continuous increase in contents of PCDD/F and PCB in flue gas was observed from superheater to inlet of air pollution control system (APCS) in Plant A, with the most significant rise noticed at air preheater. The load of PCDD/F and dioxin-like PCB in ashes also amplified steadily along the cooling path of flue gas in both plants. Changes in formation pathways are discussed based on homologue and isomer distribution patterns.

Retracted: Application of Reinforcement Learning Algorithm Model in Gas Path Fault Intelligent Diagnosis of Gas Turbine.

[This retracts the article DOI: 10.1155/2021/3897077.].

A Discrete Cosine Transform-Based Rapid Algorithm for High-Resolution, Full-Spectrum Calculations Over Inhomogeneous Gas Paths

A Discrete Cosine Transform-Based Rapid Algorithm for High-Resolution, Full-Spectrum Calculations Over Inhomogeneous Gas Paths

Effect of associated gas utilization on the creep life of gas turbines employed for power generation application

Utilizing associated gas (A-Gas) in gas turbines for power generation applications would greatly solve some of the acute power challenges Nigeria is faced with over the years. However, utilizing A-Gas to generate a given power demand, would necessitate the engine fired with associated gas to consume more fuel; thereby causing the engine to operate at elevated turbine entry temperatures, which may affect the creep life of the turbines. This study investigates the effect of associated gas utilization on the creep life of gas turbines. GasTurb details 5.1 was employed to model the A-Gas fuel, while GasTurb 11 was used to model and simulate the performance of the aero-derivative gas turbine engine fired with natural gas and associated gas separately. The input and output gas path parameters obtained from GasTurb simulations which include mass flow rate, Pressure ratio, turbine entry temperature, engine rotational speed, power output etc. were used as input to size the HP turbine Blade. Larson Miller parameter and blade metal temperatures obtained for different sections of the blade were used to estimate the time to failure of the HP turbine blade for the two conditions (blade of engine fired with natural gas and A-gas separately) investigated. The results show that the estimated time to failure of the HP turbine blades for engine fired with natural gas is 49,821.4 h as against 33,158 h for the one operated with A-Gas fuel.

Residual stress and microstructure in IN718-René41 graded superalloy fabricated by laser blown directed energy deposition

Additively printed Ni-based superalloy with a compositionally graded transition from IN718 to René41 was fabricated by laser blown-powder directed energy deposition (DED/LB-M), with the goals of meeting location-specific temperature capability and reducing component cost for hot gas path turbine components. Residual stress distribution in thin wall specimens with three sets of DED build parameters in the as-built and stress-relieved states was measured by neutron diffraction. For calculating residual stress, the calculated d0 method was found to be more appropriate as stress-free reference than using the lattice spacing measured from the stress-relief heat treated specimens. Longer dwell time (lower interpass temperature), higher energy input, smaller layer thickness resulted in a higher magnitude of tensile residual stresses at edges and compressive residual stresses at center of the specimens. The residual stress results did not show a strong dependence on graded compositions, indicating that the residual stress build-up was more geometry and process dependent. Non-destructive neutron imaging based on the attenuation coefficient qualitatively visualized the compositional variation in the bulk and showed good agreement with quantitative Electron Probe Micro-Analysis (EPMA) measurement. Grain structure, texture, and residual plastic strain along the build direction were characterized by Electron Backscatter Diffraction (EBSD). Long columnar grains with (001) preferred grain orientation were dominant along the build direction. Compositional change did not show an obvious effect on the epitaxial growth of dendrites and the continuation of the columnar grains. Residual plastic strain was relatively low in the as-built specimens.

A hierarchical structure built on physical and data-based information for intelligent aero-engine gas path diagnostics

Future trends in engine health management (EHM) systems are information fusion, advanced analytical methods, and the concept of the Intelligent Engines. Machine Learning (ML)-based aero-engine gas path diagnostic methods are promising under the motivation of these trends. However, previous ML-based diagnostic structures are rarely applied in actual engineering practice because they are purely mathematical and lack physical insight or are limited by the error accumulation problem. Developing an accurate, flexible and interpretable intelligent diagnostic method has always posed a challenge, especially when physical knowledge is also available for more diagnostic information. Instead of modifying and applying existing ML methods for classification or regression, this study proposes a novel hierarchical diagnostic method to get insight into the physical systems, build hierarchies automatically, and recommend the classification structures. The proposed hierarchical diagnostic method is evaluated against a NASA model high-bypass two-spool turbofan engine. NASA's blind test case results show that Kappa Coefficient of the proposed hierarchical diagnostic method is 0.693 and is at least 0.008 higher than the other diagnostic methods in the open literature. It has been proved that the proposed method can quantify the dependence relationships between the fault classes for enhanced diagnostic information, recommend the best diagnostic structure for reduced complexity, and solve the error accumulation problem for improved diagnostic accuracy. The proposed method could support intelligent condition monitoring systems by effectively exploiting physical and data-based information for improved model interpretability, model flexibility, diagnostic visibility, diagnostic accuracy, and diagnostic reliability.